Educational and Clinical Applications of a Web- and Android-Based Telemedicine Platform to Expand Rural Health Care in Ecuador by Leonel Vasquez-Cevallos, Andrew Mitchell, Susana Muñoz-Hernández, Ángel Herranz-Nieva, Ana Garcia-Mingo, Paula De Corral-San Martin, Mijail Castro, Paul E.D. Soto-Rodriguez, Franklin Parrales-Bravo, Rosangela Caicedo-Quiroz

“…Materials and Methods: A mixed-methods approach was used, including technical, clinical, and educational validation. Technical validation involved 10 general practitioners and five specialists who evaluated task completion times, error rates, and user satisfaction. …”
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Examining Occupational Stress and its Related Factors in Nurses Working in the Educational Hospitals of Kashan University of Medical Sciences by Hamidreza Gilasi, Fatemeh Mohebbi, Najmeh Sharifi

“…Background: Long-term occupational stress can lead to an increase in clinical errors and negative effects on nurses’ health. This study aims to investigate occupational stress and its related factors in nurses working in the educational hospitals of Kashan University of Medical Sciences. …”
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Impact of digitization on educational management: Results of the introduction of a learning management system in a traditional school context by Alex Pacheco, Renato Yupanqui, Diana Mogrovejo, Joel Garay, Yrene Uribe-Hernández

“…Prior to the pandemic, educational institutions maintained traditional practices in academic management, limiting the efficiency and quality of learning in an increasingly digital environment. …”
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Clinical Competency in Anesthesia Nursing Education: A Descriptive Cross-Sectional Study at Jundishapur University of Medical Sciences by Ali Khalafi, Sajjad Choopani, Nooshin Sarvi-Sarmeydani

“… Background: Clinical competence is an essential attribute for anesthesia nurses, as it directly influences patient safety, minimizes medical errors, and enhances surgical outcomes. In Iran, ensuring the clinical competence of anesthesia nurses is vital to addressing the growing demands of modern healthcare. …”
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To make schools free from classrooms and lessons or descholarize education -about Bogusław Sliwerski`s and Michał Paluch`s book by Magda Karkowska

“…The purpose of the authors of the book is to restore the right to freedom in education, which is a guarantee of its quality based on perpetration, responsibility, and the participation of students, teachers and parents as entities forming the educational community. …”
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Optimization of multi-objective feature regression models for designing performance assessment methods in college and university educational reform by Fengjun Qi, Zhenping Liu, Wenzheng Zhang, Zhenjie Sun

“…Experimental evaluations on three datasets—Education Reform (EDU-REFORM), Programme for International Student Assessment (PISA), and National Assessment of Educational Progress (NAEP)—demonstrate the superior performance of MOFR-LSF, achieving relative root mean square error (RRMSE) values of 0.634, 0.332, and 0.925, respectively, outperforming existing multi-objective regression algorithms. …”
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Development and psychometric evaluation of the nurses’ competency in patient education scale: a sequential exploratory mixed-method study by Zahra Farsi, Reza Momen, Seyedeh Azam Sajadi, Reza Negarandeh

“…Abstract Introduction Competency in patient education is one of the main elements of nurses' professional competency. …”
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THE CLINICAL CONFERENCE AS GUIDANCE TO FORMING INTERNS’ PROFESSIONAL COMPETENCIES DURING FORMATION IN THE UMSA’S DEPARTMENT OF POSTGRADUATED EDUCATION OF DENTISTS by T.P. Skripnikova, M.V. Khrebor, Ju. I. Sylenko, O.A. Pisarenko

“… Over 25 years the staff of the department of postgraduate education of dentists of the "UMSA" has been preparing the interns. …”
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Prediction of teaching quality in the context of smart education: application of multimodal data fusion and complex network topology structure by Chunzhong Li, Chenglan Liu, Wenliang Ju, Yuanquan Zhong, Yonghui Li

“…The prediction model based on attention mechanism optimized deep neural network achieved an average accuracy of 94.16% in the first test; the average F1 score was 90.60%; the AUC (Area Under the Curve) value was 0.975; the average mean square error was 0.271. The attention mechanism optimized deep neural network teaching quality prediction model studied in this article has improved the accuracy and reliability of prediction, achieving comprehensive and accurate prediction of teaching quality.…”
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Psychometric Properties of a Neuropsychological Assessment Scale for Diagnosing Alzheimer's Disease in the Illiterate and Low-Educated Subjects in Iran by Ameneh Ahmadi, Maryam Noroozian, Mohsen Kachooei, Zahra Hooshyari, Aram Golsokhan

“…Results: Confirmatory factor analysis showed that all questions significantly loaded on their respective factors, effectively measuring their intended constructs. The root mean square error of approximation (RMSEA) was less than 0.08, indicating a good model fit and supporting the scale's validity. …”
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Psychometric validation of the Physician Well-Being Index-Expanded (ePWBI) among physician educators in Hong Kong by Linda Chan, Paul Po Ling Chan, Xiaoai Shen, Emma Victoria Marianne Bilney, Tai Pong Lam, Julie Yun Chen, George L. Tipoe, Fraide A. Ganotice

“…Introduction Physician educators’ distress and well-being are of emerging concern in academic medicine. …”
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Adaptación, validación e invarianza factorial de una escala para evaluar la calidad de los cursos virtuales desarrollados para estudiantes peruanos de ciencias de la salud durante... by Claudio Intimayta-Escalante, Rubí Plasencia-Dueñas, Janeth N. Nuñez-Lupaca, Kevin Flores-Lovon, Nancy Ramirez-Bernuy, Giancarlo Pares-Ballasco, Natalia Barrientos-Odias, Ronald Castillo-Blanco

“…La validez basada en la estructura interna se evaluó con los índices de bondad de ajuste (IBA) en el análisis factorial confirmatorio (AFC), considerando adecuado el índice de ajuste comparativo (CFI) y el índice de Tucker-Lewis (TLI) mayor a 0,90; así como valores de la raíz residual estandarizada cuadrática media (SRMR) y el error cuadrático medio de aproximación (RMSEA) menores a 0,08. …”
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Integrating AI into clinical education: evaluating general practice trainees’ proficiency in distinguishing AI-generated hallucinations and impacting factors by Jiacheng Zhou, Jintao Zhang, Rongrong Wan, Xiaochuan Cui, Qiyu Liu, Hua Guo, Xiaofen Shi, Bingbing Fu, Jia Meng, Bo Yue, Yunyun Zhang, Zhiyong Zhang

“…Binary regression analysis was used to explore factors affecting the Trainees’ ability to identify errors generated by ChatGPT-4o. Results A total of 137 participants were included, with a mean age of 25.93 years. …”
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Effectiveness of tailored educational content on improving nurses’ clinical performance in cardiac surgery wards: a mixed-methods study by Hadi Kazemi-Arpanahi, Khadijeh Moulaei, Ferdos Hadideh, Zahra Gorjian, Alireza Baghrobehbahani, Maryam Heidari, Noorollah Tahery, Mohammadsadegh Aghili Nasab, Sara Sayar, Mahsa Tafazoli, Raha Tabahfar, Zeinab Nassari, Farshid Mohammad Mousaei, Elham Mohammadi Darvishvand, Mohsen Shafiee

“…The significance of nurses’ performance in this field is paramount due to the potential consequences of errors. Therefore, nurses in cardiac intensive care units (C-ICU) must consistently undergo essential training to minimize errors and enhance their skills. …”
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A reanalysis of the Institute for Research and Evaluation report that challenges non-US, school-based comprehensive sexuality education evidence base by Kelly VanTreeck, Shatha Elnakib, Venkatraman Chandra-Mouli

“…Comprehensive sexuality education (CSE) prepares young people to make informed decisions about their sexuality. …”
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Assessment of Healthcare Practitioners’ Attitudes toward Patient Safety in Hospital Settings in Saudi Arabia: A Strategy to Improve Medical Education by Abdulkarim Jayiz M. Alruwaili, Saad Dawood S. Alkubaydan, Jamal Muqbil B. Alshammari, Ibrahim Homoud E. Alkhaldi, Rayan Saud S. Alsharari, Marwa Ahmed El Naggar

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Patient safety education in Umm Al-Qura dental school: A comprehensive analysis of curriculum content and student confidence by Salwa A. Aldahlawi, Hanadi S. Lingawi, Ibtesam K. Afifi

“…Areas such as interprofessional education, clinical risk management, learning from errors, and teamwork should be augmented.…”
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Ajouts, omissions, substitutions : la main fautive des copistes dans le texte de L’Éducation sentimentale by Pierre-Marc de Biasi, Déborah Boltz

“…We will try to show with precise examples how these errors – of all kinds (additions, omissions, substitutions, displacements…) – have in many ways modified the very reading of the text of the Éducation sentimentale. …”
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Mathematical Modeling Approach to Assessing Math Education Levels in Secondary and High Schools: Pandemic Impact and Post-Pandemic Projections by Sakar Ismael Gharib, Bilgen Kaymakamzade, Ahmet Karahan, Murat Tezer

“…This study compares the views of mathematics teachers in private and public schools on mathematics education during the COVID-19 pandemic from their perspectives after the pandemic, focusing on factors influencing secondary and high school mathematics education. …”
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Intelligent long jump evaluation system integrating blazepose human pose assessment algorithm in higher education sports teaching by Tao Wang

“…Additionally, the method shows a scoring result with an average error range of 3 points compared to evaluations by professional teachers. …”
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